What is the best course for LangChain?

The best LangChain course offers both foundational theory and hands-on practice, covering architecture, memory, chains, prompts, and integrations with models like Flan T5 or GPT—ideal for building real-world AI applications.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

LangChain and Workflow Design Course

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LangChain and Workflow Design Course

This course is part of LLM Application Engineering and Development Certification Specialization

Instructor: Priyanka Mehta

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understand LangChain architecture and its core components like chains, memory, and prompts
Build and deploy GenAI workflows using LangChain and advanced LLMs
Integrate LangChain with models like Hugging Face’s Flan T5 XXL
Apply LangChain to real-world use cases with a focus on scalability and security

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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This course is part of the LLM Application Engineering and Development Certification Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

This LangChain for Generative AI course equips you with the skills to build and deploy reasoning-driven applications using large language models. Begin with the foundations—understand the background, key concepts, and architecture of the LangChain framework, including components like memory, chains, prompts, and text embedding models. Progress to hands-on application—learn how to design and integrate generative workflows using LangChain, explore system requirements and privacy features, and build real-world pipelines with models like Hugging Face’s Flan T5 XXL. Discover industrial use cases from platforms like Beautiful.ai and Bardeen.ai.

To be successful in this course, you should have a basic understanding of Python, APIs, and foundational language model concepts. By the end of this course, you will be able to: - Understand LangChain fundamentals and reasoning-based architecture - Build GenAI pipelines using memory, prompts, and chains - Apply LangChain in real-world workflows and integrations - Deploy secure, scalable GenAI applications using LangChain Ideal for developers, AI engineers, and data professionals building with large language models.

Explore the foundations of LangChain in this module designed for developers building with large language models. Learn the background, key concepts, and supported programming languages. Understand the architecture of the LangChain framework, including components like memory, chains, text embedding models, and prompts, all designed for reasoning-driven GenAI applications.

What's included

10 videos1 reading3 assignments

10 videos Total 49 minutes

Learning Objectives 1 minute
Background of LangChain 7 minutes
LangChain: Key Concepts 7 minutes
Compatibility Programming Languages 2 minutes
LangChain: Framework 4 minutes
LangChain Framework Driven by Reasoning 4 minutes
LangChain Components 6 minutes
Text Embedding Model and Prompt 6 minutes
Memory and Chain in LangChain 7 minutes
Architecture of LangChain Framework 6 minutes

1 reading Total 10 minutes

Course Syllabus 10 minutes

3 assignments Total 70 minutes

Quiz on Introduction to LangChain 15 minutes
Quiz on Architecture of LangChain 15 minutes
Assessment for Foundations of LangChain 40 minutes

Learn to apply LangChain for building powerful Generative AI workflows in this hands-on module. Explore system requirements, core features, and security practices of LangChain. Understand how to design and integrate generative workflows into existing systems. Gain practical experience with a demo using Hugging Face’s Flan T5 XXL model, and discover real-world applications like Beautiful.ai and Bardeen.ai.

What's included

10 videos4 assignments

10 videos Total 67 minutes

System Requirements for LangChain 6 minutes
Features of LangChain 5 minutes
Data Privacy and Security 6 minutes
Demo: Building a Text Generation Pipeline with LangChain and Hugging Face’s Flan T5 XXL Model 20 minutes
Workflow Generative AI Applications 7 minutes
Workflow Traditional Applications 3 minutes
Workflow Traditional vs. Generative AI 6 minutes
Generative AI Integration into Existing Workflows 6 minutes
Industrial Application: Beautiful.ai and Bardeen.ai 6 minutes
Key Takeaways 1 minute

4 assignments Total 85 minutes

Quiz on Working with LangChain 15 minutes
Quiz on A Comprehensive Overview of LangChain 15 minutes
Quiz on Designing Workflow for Generative AI Applications 15 minutes
Assessment for Applying LangChain for Generative AI Workflows 40 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Priyanka Mehta

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Frequently asked questions

Top LangChain courses cover its architecture, components like chains and memory, and practical integration with LLMs like OpenAI and Hugging Face. Look for hands-on content that includes real-world demos and workflow design.

LangChain is used to build applications powered by large language models. It helps developers create reasoning-driven GenAI workflows by chaining together prompts, models, tools, and memory components.

Beginners should start by understanding LLM basics and Python. Then, follow a structured LangChain course that introduces its architecture, components, and step-by-step implementation with small GenAI projects.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.